Abstract
In later years, different environmental phenomena have attracted the attention of artificial intelligence and machine learning researchers. In particular, several research groups have applied genetic algorithms and artificial neural networks to the analysis of data related to atmospheric and environmental sciences. In the current work, the results of applying the Gamma classifier to the analysis and prediction of air quality data related to the Mexico City Air Quality Metropolitan Index (IMECA in Spanish) are presented.
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Yáñez-Márquez, C., López-Yáñez, I., de la Luz Sáenz Morales, G. (2008). Analysis and Prediction of Air Quality Data with the Gamma Classifier. In: Ruiz-Shulcloper, J., Kropatsch, W.G. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2008. Lecture Notes in Computer Science, vol 5197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85920-8_79
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DOI: https://doi.org/10.1007/978-3-540-85920-8_79
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